Can Gemma 3 4B run on RX 6600 8GB?
YES — Runs Great
Gemma 3 4B needs ~6.2 GB VRAM. RX 6600 8GB has 8.0 GB. With Q4_K_M quantization, expect ~36 tok/s.
Operating mode
Choose the run profile you care about
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
35.8 tok/s
TTFT
5408 ms
Safe context
30K
Memory
6.2 GB / 8.0 GB
Memory breakdown
See how fast it feels
What limits this setup
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 35.8 tok/s | 2950 ms | 30K |
| Coding | A | Runs well | 35.8 tok/s | 5408 ms | 30K |
| Agentic Coding | A | Runs with offload (needs ~0.1 GB host RAM) | 24.9 tok/s | 11307 ms | 30K |
| Reasoning | A | Runs well | 35.8 tok/s | 6392 ms | 30K |
| RAG | A | Runs with offload (needs ~0.1 GB host RAM) | 24.9 tok/s | 14133 ms | 30K |
Quantization options
How Gemma 3 4B (4B params) fits at each quantization level on RX 6600 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 1.6 GB | Low | A72 |
Q3_K_S | 3 | 2.0 GB | Low | A73 |
NVFP4 | 4 | 2.2 GB | Medium | A73 |
Q4_K_M | 4 | 2.4 GB | Medium | A74 |
Q5_K_M | 5 | 2.9 GB | High | A75 |
Q6_K | 6 | 3.3 GB | High | A75 |
Q8_0Best for your GPU | 8 | 4.3 GB | Very High | A74 |
F16 | 16 | 8.2 GB | Maximum | F0 |
Get started
Copy-paste commands to run Gemma 3 4B on your machine.
Run
ollama run gemma3:4bYour hardware
More models your RX 6600 8GB can run
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 👁 Alibaba Qwen 3.5 9B | 9B | A | 11.5 tok/s | |
| 👁 Alibaba Qwen 3 8B | 8B | A | 14.9 tok/s | |
| 👁 NVIDIA Nemotron Nano 8B | 8B | A | 15.8 tok/s | |
| 👁 InternLM InternVL2 8B | 8B | A | 15.8 tok/s | |
| 👁 Mistral Ministral 3 8B | 8B | B | 14.9 tok/s |
